Machines are making faster and better decisions than humans about business and personal matters.
Artificial intelligence (AI) has come a long way. While our parents grew up with the dream to one day roam with robots, today we are interviewing Sophia, a citizen of Saudi Arabia, who is also the first humanoid robot to be granted a citizenship in any country. Deep learning, a brain-inspired discipline of AI has been around for a long time but has only recently taken off due to abundant data, plus advances in the Internet, machine learning algorithms and hardware accelerators. Critical decisions that used to take traditional trial and error experiments months and years to confirm are now taking minutes to hours with machine learning algorithms. Humans are relying more and more on machine learning to make better and faster business and personal decisions.
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Experts at the Table, part 1: Shrinking features isn’t enough anymore. The big challenge now is how to achieve economies of scale and minimize complex integration issues.
Rising costs and gaps in equipment emerge as technology scales; new tools under development.
Combining the flexibility of a FPGA with the performance and cost benefits of an SoC is pushing this technology well into the mainstream.
Explosion of data is forcing significant changes in where processing is done.
Researchers digging into ways around the von Neumann bottleneck.
Showing that a processor core adheres to a specification becomes more difficult when the specification is extensible.
Optimizing complex chips requires decisions about overall system architecture, and memory is a key variable.
Why data scrubbing and social issues could limit the speed of adoption and the usefulness of this technology.
Wally Rhines, Mentor’s CEO Emeritus, points to big shifts caused by AI, customization, uncertainty in the global economy and a changing customer base.
Combining the flexibility of a FPGA with the performance and cost benefits of an SoC is pushing this technology well into the mainstream.
Smaller features and AI are creating system-level issues, but traditional ways of solving these problems don’t always work.
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